NSF Award
2431213
Historically, water systems in urban communities have been thought about, regulated, and managed as three distinct sub-systems: drinking water, wastewater, and stormwater. Practitioners throughout the world are increasingly embracing the idea of integrated management of these three subsystems with the end goals of improving water quality, increasing water supply reliability, reducing freshwater withdrawal, and achieving energy and cost savings. However, widespread adoption of this integrated “One Water” vision will require a radical departure from the siloed way these systems are typically managed. This CIVIC project will foster a technology- and community-centered approach for managing cascading water quality risks in the Occoquan Reservoir, a source of drinking water for up to 1 million people in Northern Virginia. To accomplish this, we will work with local communities to identify concerns and potential solutions to the water quality challenges facing this critical water supply. We will then pilot test a new water quality modeling framework with our community partners. The modeling framework will serve as the centerpiece of a generalizable system-of-systems approach for managing emerging contaminants and other acute and chronic water quality challenges in One Water systems.<br/><br/>Our vision for managing water quality risks in One Water systems is predicated on an ability to link upstream pollution sources to downstream water quality, ideally in real time. Models of pollutant fate and transport through reservoirs typically take the form of software packages that numerically solve momentum, energy and mass conservation equations, empirical models, machine learning approaches, or multi-model ensembles. The approach proposed here, transient transit time distribution (T-TTD) theory, takes an entirely different tack by tracking the flux and age distribution of water and pollutants moving into and out of a control volume drawn around the reservoir. By eliminating the need to describe within reservoir transport processes, T-TTD theory vastly simplifies model development, reduces computational requirements for real-time deployment, and opens the door to unbiased assessment of model structure and parameter inference. It is also strongly data driven and thus leverages the high-frequency flow and water quality monitoring data routinely collected in One Water systems. Co-production of this modeling framework will ensure that it is salient, credible, and legitimate for decision-making. The goal is to provide communities and practitioners with the actionable information they need to manage cascading water quality risks in more integrated and equitable ways, both now and under various population growth and climate change scenarios.<br/><br/>This project is in response to the Civic Innovation Challenge program’s Track A. Climate and Environmental Instability - Building Resilient Communities through Co-Design, Adaption, and Mitigation and is a collaboration between NSF, the Department of Homeland Security, and the Department of Energy.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
